1. Field of the Invention
The present invention relates to the field of volume visualisation, and more particularly without limitation to volume rendering.
2. Prior Art
Volumetric data is typically a set S of samples (x, y, z, v), representing the value v of some property of the data, at a 3D location (x, y, z). If the value v is simply a 0 or a 1, e.g. with a value of 0 indicating background and a value of 1 indicating the object, then the data is referred to as binary data. The data may instead be multivalued, with the value representing some measurable property of the data, including, for example, colour, density, heat or pressure.
In general, samples may be taken at purely random locations in space, but in most cases the set S is structured, containing samples taken at regularly spaced intervals along three orthogonal axes. When spacing between samples along each axis is a constant, the set S is isotropic. If there are different spacing constants for the three axes, the set S is anisotropic. Since the set of samples is defined on a regular grid, a 3D array (called also volume buffer, cubic frame buffer, 3D raster) is typically used to store the values, with the element location indicating position of the sample on the grid. Alternatively, rectilinear, curvilinear (structured), or unstructured grids are employed. In a rectilinear grid the cells are axis-aligned, yet grid spacings along the axes might be arbitrary.
Volume visualisation is a method of extracting meaningful information from volumetric data. Volume data are obtained by sampling, simulation, or modelling techniques. For example, a sequence of 2D slices obtained from magnetic resonance imaging (MRI) or computed tomography (CT) is 3D reconstructed into a volume model and visualised for diagnostic purposes or for planning of treatment or surgery. In many computational fields, as in fluid dynamics, the results of simulations typically running on a supercomputer are often visualised as volume data for analysis and verification. In addition, many traditional geometric computer graphics applications, such as CAD and simulation, as well as applications mixing geometric objects with medical data have exploited the advantages of volume techniques for visualisation.
Volume rendering is the process of creating a 2D image directly from 3D volumetric data. Volume rendering can be achieved using an object-order, an image-order, or a domain-based technique. Object-order volume rendering techniques use a forward mapping scheme where the volume data is mapped onto the image plane. In image-order algorithms, a backward mapping scheme is used where rays are cast from each pixel in the image plane through the volume data to determine the final pixel value. In a domain-based technique, spatial volume data is first transformed into an alternative domain, such as compression, frequency, and wavelet, and then a projection is generated directly from that domain.
For an overview of various prior art volume rendering techniques reference is made to ‘Handbook of medical imaging, processing and analysis’, Isaac N. Bankman, Academic press 2000.
An important field of application of volume visualisation techniques is medical imaging, such as imaging of MRI or CT image data.
For example, the number of slices acquired in thorax CT scans is strongly increasing with advances in scanner technology. Current clinical scanners may produce more than 400 slices at resolution 512×512. Lab versions of scanners produce up to 2000 slices of size 1024×1024. The conventional way of looking at single axial slices for diagnostic purposes is very tedious, time consuming and error prone. Volume rendering techniques (VRT) are therefore increasingly popular in reading multi-slice thorax scans.
Therefore a need exists for providing an improved method of volume visualization.
Payne B. A. et al: “Distance Field Manipulation of Surface Models” IEEE Computer Graphics and Applications, IEEE Inc. New York, US, vol. 12, no. 1, 1992, pages 65-71, XP000282008, ISSN:0272-1716 shows a surface manipulation technique that uses distance fields, i.e. scalar fields derived geometrically from surface models, to combine, modify and analyze surfaces.
Suya You et al: “Interactive volume rendering for virtual colonoscopy” IEEE Conference on Visualization, Los Alamitos, Calif.: IEEE Computer Soc, US, vol. Conf. 8, 19 October 1997 (1997-10-19), pages 433-436, 571, XP010270139, ISBN: 0-8186-8262-0 shows the system for interactive virtual colonoscopy. The system enables a user to interactively navigate inside a virtual colon world in a manner similar to optical colonoscopy.
A common disadvantage of such prior art system is that the interactive navigation mode that is provided is not intuitive and difficult to use.